An indoor positioning system (IPS) is a system that generates and provides indoor position information within a building, complex, facility or community to receivers possessed or held by visitors. In large public buildings or facilities such as transport hubs, major hospitals, museums and large department stores, such indoor position information may be provided to mobile receivers, for people who wear them to locate themselves or to receive useful information regarding their location. An indoor positioning system is useful during normal times and is essential during emergencies.
Specifically, an indoor position system serving large public buildings during normal times and emergencies must have the following four attributes: First, the system must be scalable. Orders of magnitude surges in crowd density and location queries may occur daily and during holidays, special occasions and emergencies. Degradation in performance in terms of location accuracy and performance time when surges occur should be small.
Second, the system must be easy to configure, deploy and maintain. Spatial, physical and functional characteristics of large public buildings and building complexes often change due to repairs, renovation and reconfiguration. It is important that updates of the IPS required to take into account the changes can be made systematically and easily. Moreover, the health of the system can be reliably monitored at low cost.
Third, graceful degradation is an essential attribute. The system should be capable of providing location information even when large parts of it are severely damaged. In particular, it should function when Internet and cell phone coverage are disrupted.
Last but not least, the capabilities required of user devices to use the service should be minimal. Ideally, any cell phone usable for originating an indoor emergency call can be used to get the caller's location sufficiently accurately.
Despite years of efforts of research communities on indoor positioning/location technologies and many major players, there is still no clear winner and no common standard today. As an evidence of the dismal state of the art, a goal stated in the road map published by US FCC (Federal Communication Commission) earlier in 2015 is to find, over the next four years, indoor mobile locating methods that can pinpoint a caller's location within about 50 meters if the call is made indoors via a mobile phone. A reason is that existing IPS typically do not work well within complex, large public buildings/facilities, such as transport hubs, major hospitals, and large department stores.
Roughly, location accuracy in the 3 to 10 meter range is achievable by systems using solely received signal strength indicator and triangularization. Such systems require only an application computing, on off-the-shelf smart phones, tablets, or laptops, the location of the device based on power of received WiFi signals from access points at known locations. This type of IPS can be expensive to maintain when the number and locations of WiFi access points change frequently. Moreover, their location accuracy may degrade when large variations in numbers and densities of people and objects they carry and carry them cause significant and unpredictable fluctuations in received signal power.
Systems aiming to provide significantly better accuracy (e.g., down to a fraction of a meter) often use non-standard protocol(s) (e.g., based on low frequency signals, ultra-wideband signals, visible light signals, acoustic signals, and magnetic fields) and/or require more sophisticated measurements. A disadvantage of these approaches is that special user devices are required. Systems that use visible light signals clearly do not work during fire emergencies.
Fingerprinting offers another way to improve locating accuracy. The term fingerprint refers to a set of location-specific values of signal power (i.e. a signal pattern). Types of fingerprints used for indoor positioning include patterns of WiFi signals from known access points, FM signals from multiple radio stations, acoustic echo patterns and background spectrum, and magnetic signatures of the building. A fingerprint-based IPS has as a part of its infrastructure a large database of fingerprints captured at different locations in the building during setup and maintenance times and a location/fingerprint server containing mappings of fingerprints to locations. To determine its own location, a mobile device sends the fingerprint captured by it at its location to the server and relies on the server to find the location(s) with matching of fingerprint(s). In addition to requiring user devices with the capability of capturing fingerprints and high cost of maintaining a database of fingerprint-to-location mappings, scalability is a serious shortcoming with all fingerprint-based systems.